Modeling of ship vertical motion with self-organizing radial basis function artificial neural network

Ships´ vertical motion caused by random disturbances of ocean wave is unsafe for navigation and carrier planes´ takeoff and landing. To reduce the vertical motion and give an effective control for ship´s motion pose, an intelligent model of ship´s vertical motion is needed. With the experimental data, based on the self-organizing radial basis function neural network, an intelligent model of vertical motion which can self-adapt with navigating speed, navigating course and ocean condition is presented. The automatic configuration and learning of the network are carried out by using a self-organizing learning algorithm. The results of simulation indicate that the performance of self-organizing radial basis function neural network is better than that of the radial basis function neural network without self-organizing learning